﻿* Encoding: UTF-8.

** Syntax reference for reproduction of data found in the dataset of: 
** Finke, P., Mueller, M., Souris, A., Sturm, R.: Representation of Partisan, Territorial, and Institutional Interests in Second Chambers: Evidence from the German Bundesrat and its Committees.

* Please see codebook for further information on variables.


* Open dataset.

* Empirical Analysis: Frequencies of all decision types and the three institutionalized, territorial conflict constellations (eastern versus western states, city states versus area states, rich versus poor states) the dataset.

FREQUENCIES dec_type, conflict_westeast, conflict_donrec, conflict_areacity.

* Table 1. Investigation periods and cases in the dataset.

FREQUENCIES inv_per.


* Table 2. Decision-making types across committees.

* Syntax shown for committee on Agricultural Policy and Consumer Protection. Repeat this step for each committee (values 1 to 14). 
* Please reload the dataset after each step.
SELECT IF committee = 1.
SORT CASES BY inv_per.
SPLIT FILE BY inv_per.
FREQUENCIES dec_type.
* Note that Table 2 shows median values to account for different lengths of investigation periods. To replicate the table, please calculate the median value of the relative share the three decision making types have in all investigation periods.

* Table 3. Decision-making types across procedures (please reload dataset here if entering commands consecutively).
* Note: Only the values for leg_proc = 105, 106, 701, 103, 201, 402, 601, 102 and 902 were used in Table 3.
SORT CASES BY leg_proc.
SPLIT FILE BY leg_proc.
FREQUENCIES dec_type.


* Table 4. Decision-making types across partisan majority constellations (please reload dataset here if entering commands consecutively).

SORT CASES BY rom.
SPLIT FILE BY rom.
FREQUENCIES dec_type.


* Figure 1. Party politics and the point in time within the federal legislative period (please reload dataset here if entering commands consecutively).
* Note: Only values for dec_type = 3 were used in Figure 1. The following six separate command clusters are in chronological order.

TEMPORARY.
SELECT IF RANGE(date,DATE.DMY(1,11,1997),DATE.DMY(31,10,1998)).
FREQUENCIES dec_type.

TEMPORARY.
SELECT IF RANGE(date,DATE.DMY(1,11,1998),DATE.DMY(30,09,1999)).
FREQUENCIES dec_type.

TEMPORARY.
SELECT IF RANGE(date,DATE.DMY(1,11,2004),DATE.DMY(30,11,2005)).
FREQUENCIES dec_type.

TEMPORARY.
SELECT IF RANGE(date,DATE.DMY(1,12,2005),DATE.DMY(30,11,2006)).
FREQUENCIES dec_type.

TEMPORARY.
SELECT IF RANGE(date,DATE.DMY(1,02,2009),DATE.DMY(31,10,2009)).
FREQUENCIES dec_type.

TEMPORARY.
SELECT IF RANGE(date,DATE.DMY(1,11,2009),DATE.DMY(31,12,2010)).
FREQUENCIES dec_type.

